Game Theory-Based Evaluation Method for Shale Compressible Logging

Abstract

A method for evaluating shale compressibility logging based on game theory, comprising: step 1: preparing rock core data, conducting experiments, and obtaining petrodynamic parameters and experimental rock physical parameters; step 2: constructing a relational expression between petrodynamic parameters and experimental rock physical parameters; step 3: constructing a relational expression for predicting void pressure in a formation based on logging rock physical parameters; step 4: constructing a relationship between laboratory and field logging rock physical parameters; step 5: constructing a geostress calculation model for a research block formation and obtaining related parameters; step 6: obtaining the main geodynamic control factor for shale compressibility by normalizing the oil extraction intensity; step 7: obtaining the main expressive parameters and ranks for shale compressibility that are relatively independent; and step 8: determining the shale compressibility index. [Effect] Established a highly accurate method for evaluating shale compressibility.

Claims

1. A method for evaluating shale compressibility logging based on game theory, comprising the following steps: Step 1: Prepare experimental rock core data, geological data, fracturing data, logging data, and production data. Perform lithological descriptions on the acquired downhole rock core data, conduct petrological-mechanical experiments, process the raw experimental data, and obtain petrological and experimental rock physical parameters. Step 2: Analyze the relationship between petromechanical parameters and experimental rock physical parameters, determine the rock physical response rules for the petromechanical parameters of the research block, and establish mathematical relationships between petromechanical parameters and experimental rock physical parameters. Step 3: Based on the geological pressure test data of the research block, analyze the correlation between the effective stress of the geological formation and the physical parameters of the logging rock, clarify the response relationship of the effective stress of the geological formation, and construct a geological void pressure prediction equation based on the physical parameters of the logging rock, by combining it with the effective stress principle. Step 4: Establish the relationship between the rock physical parameters in laboratory experiments and the rock physical parameters in field logging. Step 5: Based on the hydraulic fracturing construction curve, and under the information constraints of the well drilling and fracturing processes, the structural strain coefficient of the research block stratum is obtained by inverse analysis using mathematical and petrological theory, utilizing a combination spring (see equations (1) and (2)), and further construct a geostress calculation model of the research block stratum to obtain the minimum horizontal principal stress, maximum horizontal principal stress and vertical stress of the research block, and further obtain the horizontal principal stress difference of the fracturing layer and the horizontal minimum principal stress difference between the intermediate layer and the fracturing layer (see equations (3) and (4), respectively). where μ is the Poisson's ratio of the rock, E is the Young's modulus of the rock (MPa), σH and σh are the horizontal maximum principal stress and the horizontal minimum principal stress (MPa), respectively, ε Ｈ , ε ｈ are the structural strain coefficients along the maximum principal stress direction and the minimum principal stress direction, respectively, H ０ is the depth of the starting point of the logging layer (m), ρ ０ (h) is the density (g / cm ３ ) at the depth h of the unlogged segment, ρ(h) is the logging density (g / cm ３ ) at the depth h, g is the acceleration of gravity (kg·m / s ２ ), △σ is the horizontal principal stress difference in the fracturing layer (MPa), σ ｈ Ｉ , σ ｈ Ｒ are the horizontal minimum principal stress in the intermediate layer and the horizontal minimum principal stress in the fracturing layer (MPa), respectively, △σ ｈ ＩＲ is the horizontal minimum principal stress difference between the intermediate layer and the fracturing layer (MPa), σ ν is the vertical stress (MPa), P ｐ is the formation pore pressure (MPa), Step 6: Normalization is performed on the extraction strength to obtain the normalized extraction strength, geomechanical parameters are extracted for each section in the borehole fracturing section, the relationship between the extracted geomechanical parameters and the normalized extraction strength is then analyzed to qualitatively understand the influence of the geomechanical parameters on the fracturing effect, the magnitude of the correlation of the influence of each geomechanical parameter on the shale fracturing effect is obtained using Gray correlation analysis, and if the correlation value exceeds 0.65, the geomechanical principal control factors for shale compressibility are obtained, and these geomechanical principal control factors for shale compressibility include the principal control factors for the fracturing layer and the principal control factors for the pressure intermediate layer, the principal control factors for the fracturing layer include the brittleness index, Young's modulus, minimum horizontal principal stress, difference in horizontal principal stress, and tensile strength, and the principal control factors for the pressure intermediate layer include the difference in horizontal minimum principal stress between the intermediate layer and the fracturing layer, the Young's modulus ratio between the intermediate layer and the fracturing layer, and the tensile strength ratio between the intermediate layer and the fracturing layer. Step 7: Using the relationship between Peason correlation coefficients and geodynamic parameters, analyze the correlation between the geodynamic principal control factors of shale compressibility, and further obtain the relatively independent principal expressive parameters and order of shale compressibility, which are the brittleness index of the fracturing layer, the horizontal minimum principal stress difference between the intermediate layer and the fracturing layer, the horizontal minimum principal stress of the fracturing layer, the horizontal stress difference of the fracturing layer, and the tensile strength of the fracturing layer. Step 8: Relatively independent principal representation parameter values ​​of different dimensions are normalized using the extreme value transformation method, where positive normalization is applied to positive indexes and negative normalization is applied to negative indexes. The positive index includes the brittleness index of the fracturing layer and the difference in horizontal minimum principal stress between the intermediate layer and the fracturing layer, and is normalized by equation (10). The negative index includes the horizontal minimum principal stress of the fracturing layer, the difference in horizontal stress of the fracturing layer, and the tensile strength of the fracturing layer, and is normalized by equation (11). Then, to determine the overall weight coefficient for the influence of different factors on shatterability, the adopted method was to calculate the weight vector, i.e., subjective weight coefficient, of each major representation parameter based on hierarchical analysis theory, determine the weight vector, i.e., objective weight coefficient, of each major representation parameter using the information entropy method, and based on this, the overall weight coefficient was obtained by comprehensively considering the subjective and objective weight coefficients of each major representation parameter based on game theory principles. Finally, the compressibility index is obtained by weighting the standardized values ​​obtained through normalization and the overall weight coefficient using the mathematical model shown in equation (5). During the ceremony, max and min represent the maximum and minimum values ​​of this type of parameter in the research block, respectively, FI is the shale compressibility index (dimensionless), S ｉ is the standardized (dimensionless) value of the main representation parameter, and w ｉ A game theory-based method for evaluating shale compressibility logging, where is the weight coefficient of the main representation parameters, their sum equals 1, and n is the number of parameters.

2. The method for evaluating shale compressible logging based on game theory, as described in claim 1, characterized in that the rock physics-rock mechanics experiment includes density tests, acoustic tests, uniaxial or triaxial compression tests, tensile strength tests and fracture toughness tests, the rock mechanics parameters include compressive strength, modulus of elasticity, Poisson's ratio, cohesive force, internal friction angle, tensile strength, brittleness index and fracture toughness, and the experimental rock physics parameters include experimental test longitudinal wave velocity, experimental test transverse wave velocity and experimental test density.

3. In step 2, a mathematical relationship was established between several petrological parameters and experimental rock physical parameters, as shown in equation (6). In the formula, σ ｃ This is the uniaxial compressive strength (MPa), and S ｔ is the tensile strength (MPa), and K ic Type I fracture toughness (MPa) m ０．５ And DEN Ｍ This is an experimental test of rock density (g / cm³). ３ ) and V ｐＭ The method for evaluating shale compressibility logging based on game theory, as described in claim 1, characterized in that is the experimental test longitudinal wave velocity (m / s).

4. In step 3, the constructed prediction relation is expressed by equation (7), In the formula, σ ν σ is the normal stress (MPa), e This is the effective stress (MPa), and P ｐ This is the void pressure (MPa) of the strata, and DEN Ｌ The density of logging rock (g / cm³) ３ ) and V ｐＬ The method for evaluating shale compressible logging based on game theory, as described in claim 1, characterized in that is the logging longitudinal wave velocity (m / s).

5. In step 4, the established relationship is expressed as follows: In the ceremony, DEN Ｍ This is an experimental test of rock density (g / cm³). ３ ) and V ｐＭ This is the experimental test longitudinal wave velocity (m / s), DEN Ｌ The density of logging rock (g / cm³) ３ ) and V ｐＬ The method for evaluating shale compressible logging based on game theory, as described in claim 1, characterized in that is the logging longitudinal wave velocity (m / s).

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